In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine. It represents the amount of time (or number of computation steps) that a "normal" physical computer would take to solve a certain computational problem using a certain algorithm. It is one of the most well-studied complexity resources, because it corresponds so closely to an important real-world resource (the amount of time it takes a computer to solve a problem).
In computational complexity theory, DTIME (or TIME) is the computational resource of computation time for a deterministic Turing machine. It represents the amount of time (or number of computation steps) that a "normal" physical computer would take to solve a certain computational problem using a certain algorithm. It is one of the most well-studied complexity resources, because it corresponds so closely to an important real-world resource (the amount of time it takes a computer to solve a problem).
The resource DTIME is used to define complexity classes, sets of all of the decision problems that can be solved using a certain amount of computation time. If problem instances of input size n can be solved in , the problem is in the complexity class {{tmath|\mathsf{DTIME}(f(n))}} (or {{tmath|\mathsf{TIME}(f(n))}}). There is no restriction on the amount of memory space used, but there may be restrictions on some other complexity resources (like alternation).
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).